# Callosum raises $100M to route AI tasks across models and chips > Source: > Published: 2026-08-20 06:40:19+00:00 # Callosum raises $100M to route AI tasks across models and chips **Bloomberg says Atomico led the early financing for Danyal Akarca and Jascha Achterberg's London startup, with Plural, DCVC and the UK's Sovereign AI Fund joining.** By [RuntimeWire Staff](/author/runtimewire-staff) ยท Published Primary source: [Bloomberg Technology](https://www.bloomberg.com/news/articles/2026-08-20/ai-startup-callosum-raises-100-million-to-make-ai-tasks-cheaper) ## Why it matters Callosum is betting the valuable layer in AI will be software that selects the cheapest workable model-chip pairing, giving it upside across hardware winners. [Callosum](https://www.callosum.com/?ref=runtimewire), the London AI infrastructure startup founded by Danyal Akarca and Jascha Achterberg, has raised $100 million in seed financing led by [Atomico](https://www.bloomberg.com/quote/3252518Z:LN?ref=runtimewire), [Plural](https://www.pluralplatform.com/features/why-we-invested-in-callosum?ref=runtimewire), and [DCVC](https://www.bloomberg.com/quote/0567226D:US?ref=runtimewire), according to [Bloomberg](https://www.bloomberg.com/news/articles/2026-08-20/ai-startup-callosum-raises-100-million-to-make-ai-tasks-cheaper?ref=runtimewire) on August 20. The UK's Sovereign AI Fund also participated, according to Bloomberg. The government-backed fund made what Callosum described as a significant investment. [Callosum did not disclose a valuation](https://www.bloomberg.com/news/articles/2026-08-20/ai-startup-callosum-raises-100-million-to-make-ai-tasks-cheaper?ref=runtimewire). The Bloomberg-reported financing follows an earlier [$10.25 million pre-seed](https://www.callosum.com/blog/introducing-callosum?ref=runtimewire) that Callosum disclosed. The founders' heterogeneous-AI thesis grew out of their neuroscience and computing research at Cambridge, as [Achterberg explained when Callosum emerged from stealth](https://www.jachterberg.com/so-why-callosum?ref=runtimewire). They argue that AI systems should combine specialized models and computing substrates rather than send every task through one general-purpose model. Callosum applies that idea to infrastructure, assigning parts of a workflow to different models, processors and cloud instances according to cost, speed and capability. The founders are taking that argument into a market built largely around homogeneous clusters of Nvidia GPUs. Callosum wants to become the routing and orchestration layer above that hardware, giving enterprises a way to combine established accelerators with newer chips without rebuilding applications around each supplier. [Callosum says](https://www.callosum.com/?ref=runtimewire) it is building for organizations deploying multi-model AI workflows and for hardware companies seeking production workloads. ### Two neuroscientists take on the AI stack Akarca trained as a medical doctor at the University of Southampton before completing a PhD in computational neuroscience at Cambridge. His doctoral work examined how brain networks develop under physical and metabolic constraints, followed by research at Cambridge's MRC Cognition and Brain Sciences Unit and Imperial College London. Achterberg completed his Cambridge PhD under neuroscientist John Duncan and Google DeepMind researcher Matthew Botvinick, with research collaborations involving DeepMind and Intel Labs. He later became a research fellow at St John's College, Oxford, studying how specialized neural circuits coordinate to produce flexible cognition. The pair's academic backgrounds are central to Callosum's architecture. Their work treated cognition as a systems problem involving specialized modules, communication constraints and distinct computational jobs. In a [company technical post](https://www.callosum.com/blog/welcome-heterogeneous-intelligence?ref=runtimewire), Callosum said a "seed model" sets a plan, sub-models handle tasks such as expansion, retrieval and verification, and the software dispatches each operation to hardware suited to its compute profile. Achterberg wrote when Callosum emerged from stealth in February that intelligence depends on ["the diversity of co-optimised mechanisms working together"](https://www.jachterberg.com/so-why-callosum?ref=runtimewire). The founders have carried that view into a product strategy that treats models and computing substrates as components software should coordinate for customers. Callosum has not publicly disclosed verified headcount, customer count, revenue or commercial deployment figures. ### The reported $100 million bet on the routing layer Callosum previously disclosed a [$10.25 million pre-seed](https://www.callosum.com/blog/introducing-callosum?ref=runtimewire) led by Plural, with participation from ARIA, the UK's Sovereign AI Fund and unnamed angel investors. The [UK government described Callosum](https://www.gov.uk/government/news/ai-firms-pioneering-drug-discovery-cheaper-supercomputing-and-more-get-first-backing-through-uks-sovereign-ai?ref=runtimewire) as the Sovereign AI initiative's first equity investment. The relationship between that earlier capital and Bloomberg's reported $100 million seed remains unclear, so Callosum's total financing cannot be stated cleanly from the available disclosures. [Callosum describes](https://www.callosum.com/?ref=runtimewire) its product as software for coordinating heterogeneous models, chips and workflows. Callosum says the system assigns different parts of a workload according to the cost, speed and capability of the available components. That position could benefit Callosum across several hardware suppliers. New accelerators need compatible software and workloads before buyers will deploy them. Enterprises, meanwhile, want lower inference bills and less dependence on a single hardware provider. Callosum is trying to serve both groups by making less-established processors usable inside production AI systems. The UK's Sovereign AI Fund is [described by the government as a fund with $677 million](https://www.gov.uk/government/publications/uk-ai-hardware-plan/uk-ai-hardware-plan?ref=runtimewire) offering equity investment, public-compute access, procurement pathways and fast-track talent visas to help British AI companies start, scale and remain anchored in the UK. Its backing puts Callosum's orchestration software inside the government's effort to build domestic influence over AI infrastructure. Callosum said in February that it was [partnering with Normal Computing, Mixx, Cortical Labs and Great Sky](https://www.callosum.com/blog/we-are-scaling-heterogeneous-compute?ref=runtimewire) on heterogeneous-compute projects. Callosum has also worked with CommonAI on a co-located heterogeneous computing project supported by a [$2.9 million ARIA grant](https://www.callosum.com/blog/we-are-scaling-heterogeneous-compute?ref=runtimewire). The projects are research-heavy, but they define the technical scope of the founders' wager: AI infrastructure will fragment beyond today's mix of GPUs and mainstream cloud accelerators. ### The benchmarks now need to become a business In a [company technical post](https://www.callosum.com/blog/welcome-heterogeneous-intelligence?ref=runtimewire), Callosum claimed that early demonstrations produced up to 12 times lower cost and 5.5 times faster performance on certain deep-context workloads. It also reported higher quality at lower cost than a single-model baseline on a partner's GitHub activity summarization task. Those figures came from Callosum's own tests, and the results vary by model, hardware pairing and workload. Callosum's commercial test is whether task-level routing can preserve those savings under production requirements such as reliability, observability and predictable pricing. Routing work among several providers creates networking and failure-management problems of its own. Customers also need clear responsibility when one component in a multi-model workflow fails. Callosum has not established a public pricing model or disclosed customers, revenue or the scale of any commercial deployments. The founders are entering a heavily financed inference market. [Baseten raised $300 million](https://www.baseten.co/blog/announcing-baseten-s-300m-series-e/?ref=runtimewire) at a $5 billion valuation in February. In a July announcement, [Fireworks AI said](https://fireworks.ai/blog/series-d-announcement?ref=runtimewire) it raised a $1.505 billion Series D at a $17.5 billion valuation. Tensormesh, which emphasizes caching and reuse of previously processed context, [raised $20 million](https://www.tensormesh.ai/blog-posts/tensormesh-raises-20m-launches-inference-platform?ref=runtimewire) in May. Infinity, which adapts inference workloads to new chip architectures, [raised $15 million](https://siliconangle.com/2026/07/20/infinity-raises-15m-run-ai-inference-chipset/?ref=runtimewire) in July. Callosum's narrower distinction is its attempt to optimize individual tasks across several models, cloud providers and types of hardware, including processors that have yet to achieve broad adoption. Callosum's reported $100 million financing would give Akarca and Achterberg capital to test whether task-level routing can lower inference costs across multiple models, cloud providers and accelerator types. Their wager depends on continued fragmentation in the AI stack. Concentration around a handful of model and hardware providers would leave Callosum with fewer differences to exploit.